# Machine Learning

### Principal Component Analysis(PCA)

Principal Component Analysis(PCA) Principal Component Analysis (PCA) is an unsupervised machine learning feature reduction technique for high-dimensional and correlated data sets. Images and text documents have high dimensional data sets which requires unnecessary computation power…

### Logistic Regression

Hyperbolic Functions These functions are very important in regression, classification and to build neural networks. Moreover, it is important to remember expression hyperbolic functions in the form of exponential functions. I have written the expressions…

### Linear Regression in Statistics

Linear regression Linear regression refers to find out degree of relationship between two variables in the form of a linear function y=mx+c using statistical techniques. Where m is gradient and c is intercept on y…

### Poisson Distribution as a Limiting Case of Binomial Distribution

For large value of n binomial distribution asymptotically tends to Poisson distribution. Probability distribution  function of binomial random variable  is Probability distribution of Poisson random variable is Poisson Distribution as a Limiting Case of Binomial…

### Exponential Probability Distribution

A random variable X is said to follow exponential distribution if it follows the following probability mass function. Exponential probability distribution is a continuous distribution. Probability Distribution Function of Exponentially Distributed Variable X   It…

### Central Limit Theorem and Normal Distribution

Why is normal distribution is important? To understand the question you have to go through the Central Limit Theorem. Central Limit Theorem According to central limit theorem if X1, X2, X3,……Xn are random variables…

### Correlation in Statistics

Correlation Correlation measures  the relation between two variables  that how they are related.  And is denoted by r and  ρ moreover, the correlation quantifies the level of relationship between -1 to +1. If the value…

### Standard Deviation, Variance and Covariance

Standard Deviation Variance and Covariance Standard deviation, variance and covariance have very important applications in machine learning and data science. Further, they are closely related to each other. In feature reduction techniques, such as PCA…

### Skewness and Kurtosis

Skewness and Kurtosis- Introduction- Skewness and Kurtosis are very important  concepts in statistics and have several applications.  In addition, they characterize the nature of data distribution which make data analysis easier. Moreover, I will separately…

### CSIR-NET Syllabus for Mathematical Sciences

CSIR-UGC National Eligibility Test (NET) for Junior Research Fellowship and Lecturer-ship COMMON SYLLABUS FOR PART ‘B’ AND ‘C’ MATHEMATICAL SCIENCES UNIT –  1 Analysis: Elementary set theory, finite, countable and uncountable sets, Real number system…